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Objectives: This study sought to report the reliability (intrasession) values of initial maximum push-rim propulsion (IMPRP) and sprint performance in elite wheelchair basketball (WB) players and to assess the involvement of strength in sprint capacity. Methods: Fifteen Spanish international WB male players participated in this study. The maximum single wheelchair push from a stationary position (IMPRP) and the sprint performance (ie, 3, 5, and 12 m) of WB players were measured in this study. Results: IMPRP mechanical outputs V, V _max, P, Rel. P, F, and Rel. F variables presented high reliability values (intraclass correlation coefficient [ICC] ≥ .92; coefficient of variation [CV] ≤ 8.04 ± 7.37; standard error of measurement [SEM] ≤ 29.92), but the maximum strength variables P_max, Rel. P_max, F _max, and Rel. F _max (ICC ≥ .63; CV ≤ 13.19 ± 16.63; SEM ≤ 203.76) showed lower ICC values and by contrast higher CV and SEM values. The most substantial correlations were identified between maximum IMPRP values (ie, V, V _max, P, Rel. P, F, and Rel. F) and sprint performance in 3 m (r ±  confidence limits ≥ −0.74 ± 0.22, very large; R ² ≥ .55), 5 m (r ±  confidence limits ≥ −0.72 ± 0.24, very large; R ² ≥ .51), and 12 m (r ±  confidence limits ≥ −0.67 ± 0.27, large; R ² ≥ .44). Conclusions: The IMPRP test and sprint tests (3, 5, and 12 m) are practical and reliable for measuring strength and speed in WB players. In addition, there were large to very large associations among strength variables (ie, P, Rel. P, F, and Rel. F) and all sprint variables. This could indicate a need to implement specific strength exercises in WB players to improve sprint capacity.

Purpose: There are important methodological considerations for translating wearable-based gait-monitoring data to field settings. This study investigated different devices’ sampling rates, signal lengths, and testing frequencies for athlete monitoring using dynamical systems variables. Methods: Secondary analysis of previous wearables data (N = 10 runners) from a 5-week intensive training intervention investigated impacts of sampling rate (100–2000 Hz) and signal length (100–300 strides) on detection of gait changes caused by intensive training. Primary analysis of data from 13 separate runners during 1 week of field-based testing determined day-to-day stability of outcomes using single-session data and mean data from 2 sessions. Stride-interval long-range correlation coefficient α from detrended fluctuation analysis was the gait outcome variable. Results: Stride-interval α reduced at 100- and 200- versus 300- to 2000-Hz sampling rates (mean difference: −.02 to −.08; P ≤ .045) and at 100- compared to 200- to 300-stride signal lengths (mean difference: −.05 to −.07; P < .010). Effects of intensive training were detected at 100, 200, and 400 to 2000 Hz (P ≤ .043) but not 300 Hz (P = .069). Within-athlete α variability was lower using 2-session mean versus single-session data (smallest detectable change: .13 and .22, respectively). Conclusions: Detecting altered gait following intensive training was possible using 200 to 300 strides and a 100-Hz sampling rate, although 100 and 200 Hz underestimated α compared to higher rates. Using 2-session mean data lowers smallest detectable change values by nearly half compared to single-session data. Coaches, runners, and researchers can use these findings to integrate wearable-device gait monitoring into practice using dynamic systems variables.

Purpose: This study aims to investigate how physical education teachers analyze their students’ swimming skills. Particular attention is given to information gathering within the diagnostic process. Methods: Data were collected from a quantitative online survey of German physical education teachers from primary and secondary schools (n = 551). This survey’s questionnaire is based on evaluated statements from a qualitative interview study (n = 10). Findings: Teachers’ diagnostic approaches vary greatly and differ in terms of quality criteria and usability. The predominant method used is movement observation, but 50.3% of the teachers do it rather rarely or without the use of criteria. Many of them (63.8%) would like to be supported by a diagnostic tool for the analysis of swimming skills. Discussion/Conclusion: It has been concluded that an accurate analysis of the students’ swimming skills as a precondition for adaptive lesson structuring is not achieved. It is necessary to determine whether a diagnostic tool could improve this process.

Purpose: To examine the effects of a neuromuscular training program combining plyometric exercises with acceleration, deceleration, and change-of-direction drills conducted on sand or hard surfaces on the fitness qualities of young male tennis players. Methods: Thirty-one young male players were allocated to a training group performing 12 training sessions on sand or hard surfaces, during a 6-week period. Tests included linear sprint (10-m acceleration with 5-m split times), change of direction (modified 5-0-5 test), vertical jumps (countermovement jump and the 10/5 repeated-jump test), isometric hip abduction and adduction strength, and dynamic balance (Y-balance test). Perceived training loads and muscle soreness were assessed during the intervention. Results: Both training strategies were similarly effective in improving the analyzed fitness components. Group × time interaction effects were noticed, with countermovement jump (P = .032), repeated-jump test (P = .029), and reactive strength index (P = .008) favoring hard surfaces and 5-m sprint (P = .009), dynamic balance (P < .05), adduction strength (P < .05), and abduction strength (P < .001) indices favoring sand. Furthermore, the sand group promoted greater perceived training loads and muscle soreness (P < .05) than the hard group across the intervention period. Conclusion: Neuromuscular training strategies characterized by a relatively low volume (∼35 min), conducted on sand or hard surfaces, promoted similar improvements in the fitness qualities of young tennis players, with selected surface-interaction effects. Training on sand can cause transiently higher training loads and persistently higher muscle soreness, suggesting the need for an adequate familiarization period.